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Machine Learning with Data Science

Live Online (VILT) & Classroom Corporate Training Course

Studying data science will help you understand how to take the raw data, analyse it, connect the dots and tell a story often via several visualizations and studying machine learning along with it will make you a specialist of artificial intelligence

Expert-Led VILT & Classroom Hands-On CloudLabs Certification Voucher Available
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Overview

Data Science and Machine Learning course will help you master the data science and analytics using different machine learning techniques and further gain deep understanding in data manipulation using R , also get introduced to hadoop architecture .

Objectives

At the end of Machine Learning with Data Science training course, participants will be able to

  • Manipulate and Visualise data using machine learning techniques
  • Write, optimize java code using Hadoop Framework

Prerequisites

A background in Java is required. This machine learning and data science course is appropriate for developers, who wish to write, maintain and/or optimize Java code using Hadoop framework. Hands on experience on writing Java programs using Eclipse editor would be a plus

Course Outline

  • Introduction
  • Understanding Big Data
  • Understand how different companies use big data for their business need
  • Big Data Challanges
  • Introduction to Data Science
  • Types of Data Scientists
  • Data Science Components
  • Data Science Use Cases
  • Introduction to R and Hadoop
  • R and Hadoop Integration
  • Machine Learning with Mahout

  • HDFS- Hadoop Distributed File System
  • Assumptions and Goals
  • CAP principle
  • Anatomy of Hadoop Cluster
  • Anatomy of a File Write
  • Anatomy of a File Read
  • MapReduce Framework Architecture
  • Hadoop Processes
  • Understanding Various configuration Properties of Hadoop

  • Introduction to R
  • Describe why R is Used?
  • Implement R programing concepts
  • Learn Data Import techniques
  • Analyze the processing of the Data

  • Observation and Experiments
  • Sampling Methods
  • Quantitative Variables
  • Skewness,Modality and Measures of Center
  • Variance, Standard Deviation, Interquartile Range
  • Probability Rules
  • Disjoint,Non Disjoint events, Independence
  • Conditional Probability
  • Probability Distributions

  • Understand Machine Learning
  • Use Cases Walkthrough
  • Machine Learning Techniques
  • Describe Clustering
  • Analyze Clustering Scenarios using Clustering Algorithms
  • Learn TF-IDF and cosine Similarity
  • Understand Supervised Learning Technique
  • Classification
  • Recommendation
  • Learn Decision Tree Classifier
  • Implement how various Decision Tree algorithms work.
  • Implement Application of Techniques on a smaller datasets for better understanding using R.
  • Understand Unsupervised Learning Technique
  • Understand the implementation of Random Forest Classifier
  • Understand the implementation of Na-ve Bayer’s Classifier
  • Apply both techniques on smaller datasets using R
  • Understand Association Rule Mining

  • Understand the need for R integration with Hadoop
  • Learn the ways to integrate R and Hadoop
  • Understand the usage of RHadoop package
  • Perform R integration with Hadoop and Run MapReduce examples

  • Understand Mahout
  • Gain insight on implementing Machine Learning with Mahout
  • Understand Learning, Classification and Clustering techniques with Mahout
  • Implement Recommendation technique and Frequent Pattern Mining in Mahout

  • Understand Mahout Algorithms and Parallel proicessing
  • Learn Advanced techniques in R
  • Implement Parallel Random Forest
  • Understand Data Visualization

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

Client Stories

What our clients say

Voices from L&D leaders, architects, and program managers who’ve trusted us with their upskilling.